I work as a forward-deployed AI engineer — embedded directly with your team to design, build, and ship production AI systems, not just advise on them. Most AI engineers can wire up an API; few understand data at depth. I do — and that combination is the whole point. My background spans 20+ years at PricewaterhouseCoopers (PwC) and Publicis Sapient — seventeen years building software, data, and machine-learning systems, and the last three focused entirely on generative AI. That lets me bridge business strategy and technical execution for Fortune 500s and growth-stage companies. Clients span ADT, Aflac, AT&T, Capital One, Carnival, Lumen (formerly CenturyLink), Eli Lilly, Fanatics, HBO, IBM, Lennar, NBCUniversal, USAA, Visa, Wells Fargo, and Worldpay. Degrees in Computer Science and Applied Statistics, plus an MBA. 𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱 Agentic AI systems — autonomous agents that reason, make multi-step decisions, and take real-world action through tools and APIs. I own the full design: LLM selection, RAG architecture, MCP server development, multi-agent orchestration, and production deployment on AWS, Azure, or GCP. The data-science layer comes built in — pipelines, predictive models, and evaluation — so agent decisions are trustworthy and measurable, not black boxes. 𝗪𝗵𝘆 𝗺𝘆 𝗯𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 𝗶𝘀 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 Most AI engineers don't understand data at depth. My foundation spans the full data-science stack — statistical inference, supervised and unsupervised machine learning, time-series, propensity scoring, customer segmentation, and marketing-mix and incrementality modeling — across financial services and fintech, insurance, telecom, healthcare and life sciences, media and entertainment, retail and e-commerce, consumer goods, and hospitality and travel. That depth changes how I build AI: models that are properly validated, pipelines designed for data quality, and outputs judged against real business metrics — not benchmark scores. 𝗦𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝘄𝗼𝗿𝗸 — 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 • ContactOS — a multi-tenant AI customer-service platform in production across voice (Twilio, Deepgram, ElevenLabs), WhatsApp, web chat, and outbound campaigns. LangGraph ReAct agents call live customer APIs in real time; per-tenant configuration via a runtime registry (a new client is a new directory, not a code change); human escalation over a WebSocket dashboard. • Replaced a specialty retailer's HubSpot CRM with a production FastAPI + React platform in weeks — built with agentic AI development tooling throughout, with AI email summarization and a shared-database architecture with the client's analytics portal, live at a fraction of the prior license cost. • Two-phase agentic engineering triage — a fast LLM classifier routes inbound tickets in under 10 seconds, then an investigation agent autonomously traces the codebase and posts structured root-cause findings to Jira. • End-to-end RAG content engine — ingests YouTube transcripts, PDFs, Kindle highlights, and web articles, then generates channel-specific content grounded in the author's own voice (not generic AI output), auto-publishing to WordPress with a companion audio file. 𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝘂𝗻𝗱𝗲𝗿𝗻𝗲𝗮𝘁𝗵 The same modeling rigor I bring to making agent decisions measurable: • Telecom propensity — scored 6.1M customers across 200+ behavioral indicators into calibrated propensity tiers, prioritizing the highest-likelihood segments to steer self-service adoption and call deflection. • Supplemental insurer media-mix — modeled a $171M media portfolio with adstock and saturation, producing per-channel ROI with credibility intervals to guide budget reallocation. • CPG segmentation — an RFM + cohort-LTV engine on Databricks classifying 83K customers weekly, driving segment-level targeting across discounting, channel, and reactivation. 𝗖𝗼𝗿𝗲 𝘀𝘁𝗮𝗰𝗸 Python · SQL · R · PySpark | LangGraph · LangChain · CrewAI · n8n · MCP Servers | Anthropic Claude · OpenAI · Ollama | Pinecone · Qdrant · ChromaDB · pgvector · mem0 | Twilio · Deepgram · ElevenLabs · Whisper | FastAPI · React · TypeScript · Docker · GitHub Actions | PostgreSQL · MongoDB · Snowflake · Redshift | dbt · Databricks | XGBoost · scikit-learn · MLflow | Tableau · Power BI · ECharts | AWS · Azure · GCP 𝗛𝗼𝘄 𝗜 𝘄𝗼𝗿𝗸 I take ownership of delivery — I scope, architect, build, and deploy, and communicate clearly with technical and business stakeholders throughout. Whether you need a solo IC or a lead to drive a small team, the approach is the same: embedded, accountable, and shipping.

Hi! I can help your business solve problems with data, from the extraction of the data until mining, analyzing, and creating machine learning models. I have experience working with ETL projects for getting data to be used at the company software, resulting in a model for detecting plagues in sugarcane plantations at 95% accuracy. I also created projects from courses and by personal initiative, targeting improvements in my abilities for data science and machine learning problems, like a project for recommending recently published videos from YouTube based on people's personal tastes at searching for videos. Since I have this experience, we can create solutions using tools like AWS, SQL, Python, scikit-learn, and many other technologies, always trying to extract the best of them and getting better results. If you are interested, let's get it! Send me a message and tell me about your project. I'll be glad to help you!

Data Engineering | Cloud Solutions (AWS/GCP/Azure) | Full Stack Java & Python Development | ETL Pipelines | Spring Boot | SQL Performance Tuning | Apache Hadoop & Spark | Snowflake | dbt | Enterprise Backend Systems I am a 𝗨𝗦-𝗯𝗮𝘀𝗲𝗱 𝗦𝗲𝗻𝗶𝗼𝗿 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗖𝗹𝗼𝘂𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝘄𝗶𝘁𝗵 𝗼𝘃𝗲𝗿 𝟴 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗹𝗲𝘃𝗲𝗹 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 building high-performance systems for Fortune 500 companies, including JPMorgan Chase and Ford Motor Company. I specialize in designing scalable backend microservices, optimizing slow databases, and architecting heavy big data pipelines that process millions of records without downtime. I don't just write code, I architect & build systems that process millions of records, reduce company costs, and stay alive at scale. ⚡ 𝗦𝗘𝗥𝗩𝗜𝗖𝗘𝗦 & 𝗦𝗧𝗔𝗖𝗞 ◆ Backend Development Java (8, 11, 17), Spring Boot, Spring Security, Spring Batch, Spring Cloud Dataflow, Hibernate, JPA, JWT Authentication, Microservices Architecture, Multi-threading, Python, FastAPI, Django, Flask, Node.js, NestJS, TypeScript ◆ Data Engineering & ETL Apache Spark, Apache Hadoop, Apache Beam, Apache Hive, Apache Airflow, GCP Dataflow, AWS Glue, dbt, SSIS, Talend, Snowflake, BigQuery, Spring Batch, Spring Cloud Dataflow, Data Ingestion Pipelines, Data Warehouse Design ◆ API & Integrations RESTful APIs, GraphQL, gRPC, WebSockets, Apigee, Swagger/OpenAPI, Payment Gateways, Google APIs, Power BI, Qlik Sense, Open Banking Connectors, Active Directory, ADFS, Zapier, Stitch ◆ Cloud & DevOps GCP (Cloud Run, Cloud Functions, BigQuery, Pub/Sub, GKE, Dataflow) AWS (Lambda, EC2, S3, RDS, Redshift, EKS, CloudWatch, CloudFormation) Azure (AKS, Sentinel, Defender for Cloud, DevOps, Landing Zones) Terraform, Kubernetes, Docker, GitHub Actions, Jenkins, Tekton, Azure DevOps, Control-M ◆ Database & Administration PostgreSQL, SQL Server, MongoDB, MySQL, Oracle, Redshift, DynamoDB, BigQuery, Redis, Snowflake, SQL Performance Tuning, Schema Design, High Availability (Always On, Failover Clustering, Log Shipping), SSRS Reporting, Backup & Recovery ◆ Full Stack Development React.js, Next.js, Node.js, Redux, TypeScript, Tailwind CSS, Angular ◆ Testing & Monitoring JUnit, Mockito, MockMVC, Jest, TDD, Integration Testing, Grafana, Splunk, GCP Cloud Monitoring, Azure Sentinel, Webex Alerting, Legacy System Cloud Migration ◆ AI & Developer Tools Claude Code, Cursor, OpenAI Codex, AI/ML Pipeline Integration, LLM-based Workflows, Intelligent Automation 📌 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 𝗜'𝗩𝗘 𝗗𝗘𝗟𝗜𝗩𝗘𝗥𝗘𝗗 ▸ Built core credit card banking microservices at JPMorgan Chase handling millions of daily transactions ▸ Architected GCP Dataflow pipelines at Ford Motor Company processing millions of records into BigQuery daily ▸ Delivered digital banking platforms powering retail and corporate banking across open banking environments ▸ Reduced ETL data processing times by over 99% for healthcare and enterprise clients ▸ Built mobile backend microservices at 𝗝𝗲𝘁𝗕𝗹𝘂𝗲 𝗔𝗶𝗿𝘄𝗮𝘆𝘀 serving thousands of daily travelers ▸ Administered high-availability database systems for federal government procurement 🏭 𝗜𝗡𝗗𝗨𝗦𝗧𝗥𝗜𝗘𝗦 Fintech · Digital Banking · Healthcare · Government · Automotive · Enterprise SaaS · Education · E-commerce · Travel & Hospitality · Open Banking ✅ 𝗣𝗘𝗥𝗙𝗘𝗖𝗧 𝗙𝗜𝗧 I work best with teams who: → Need Java or Python expertise without hand-holding → Have APIs, pipelines, or databases that need fixing or scaling → Are building on AWS, GCP, or Azure and need someone who knows these environments → Want clean maintainable code delivered on time → Need a developer who can also talk to clients and stakeholders professionally I communicate clearly, deliver on time, and bring Fortune 500 engineering standards to every project regardless of size. Ready to build something that scales? Send me a message or 𝗰𝗹𝗶𝗰𝗸 𝗜𝗻𝘃𝗶𝘁𝗲 𝘁𝗼 𝗝𝗼𝗯. I respond within a few minutes. Java Developer · Python Developer · Backend Developer · Data Engineer · ETL Developer · Spring Boot · Cloud Architect . Cloud Engineer . Cloud Migration. Azure Enginer . AWS. GCP . FastAPI · Django · Flask · REST API · GraphQL · Microservices · Apache Spark · Apache Airflow · dbt · Snowflake · AWS · GCP · Azure · Terraform · Kubernetes · Docker · PostgreSQL · SQL Server · MongoDB · Node.js · React.js · Full Stack Developer · Cloud Architect · API Integration · Data Pipeline · Data Warehouse · CI/CD · BigQuery · Kafka · Redis · Rabbi

I am a data-driven software engineer with many years of experience in the platform, specializing in business intelligence and dashboard development. My expertise lies in transforming complex data into clear, actionable insights that drive informed decision-making. With a strong background in Power BI, Looker Studio, and various data engineering tools, I deliver comprehensive solutions that empower businesses to optimize their operations. Core Expertise Looker Studio Dashboard Development Power BI Dashboard Development Data Visualization and Storytelling Data Engineering and ETL Processes SQL Query Optimization and Data Modeling Python Scripting for Data Automation Technical Skills Visualization: Power BI, Looker Studio, Metabase Databases: BigQuery, PostgreSQL, MySQL, SQL Server Programming: Python (pandas, django, scrapy), SQL Data Engineering: DBT, Prefect Cloud Platforms: Heroku, GCP Professional Experience I have worked with various clients across different industries, including: Business Intelligence Analyst: Developed and maintained BI reports and dashboards using Power BI, SQL, and DBT. Google Data Studio & BigQuery SQL Specialist: Created data visualizations and reports, designed and implemented KPIs using DBT. These experiences have honed my ability to deliver impactful data solutions across diverse business contexts. Services Offered Power BI: Creation of interactive dashboards Data source integration and transformation Custom visualizations and DAX calculations Looker Studio: Creation of interactive dashboards Data source integration and blending Custom visualizations and calculated fields Data Engineering: Data pipeline construction and ETL processes using DBT and Prefect Data modeling and database design Data Automation: Python scripting for data ingestion and automation API integration and web scraping

🚫 Stop Patching. Start Scaling. Spreadsheets, Zapier chains, and half-working GPT prompts can feel like control. In reality, they are what is holding you back. You don’t need more hacks. You need real AI infrastructure: systems that are scalable, safe, and built to last. I help teams diagnose the chaos, design the fix, and deploy AI-powered automations that actually move the needle - from intake optimization to agent copilots to real-time CRM nudges. ⸻ 🔧 What You’ll Get AI Automations That Work (and Last) • LLM-augmented intake flows for forms, chats, and CRMs • RAG (Retrieval-Augmented Generation) for instant internal knowledge access • Live Google Sheets enrichment with AI lookups • Workflow orchestration with n8n, Clay, Zapier, or a custom stack Copilot Agents That Teams Actually Use • GPT-powered assistants in Slack, Notion, or Google Chat • Instant doc search and embedded QA tools (<3s latency) • Auto-summarization for cases, leads, or tickets to speed triage • Human-in-loop oversight with audit trails and confidence scores Lead Research & Data Activation • Custom lead pull workflows with Clay, Browserbase, or OpenAI • Automatic ICP scoring, segment tagging, and outreach prep • CRM enrichment with context, buying intent, and recommended actions • Personalized outreach draft flows for SDR teams ⸻ 🏆 Why Teams Trust Me • Led AI rollouts across legal, healthcare, DTC, and real estate • Helped clients cut case handling time by 30%, deploy 20+ AI agents, and ship copilots used daily by 25+ reps • Every build is documented (Looms, Notion, Slack) so your team learns, not just uses • No black boxes. Everything is inspectable, versioned, and scalable ⸻ 🛠 Tools I Run On Workflow & Automation: n8n, Zapier, Clay, Browserbase, AirOps LLM & RAG Infrastructure: OpenAI, Firecrawl, Relevance AI, LangChain Data Enrichment & Modeling: dbt, Snowflake, BigQuery, Google Sheets, Segment CRM & Activation: HubSpot, Klaviyo, Customer.io, Hightouch, Census Communication & Enablement: Slack, Notion, Linear, Loom ⸻ 📂 Proof in Action • Call Center Copilot: Slack-native AI agent that cut training time & error rates by 90% • Legal Medical Record Assistant: Summarized intake + records, reducing triage from 10 days to <2 weeks • Retail Monitoring System: 900+ stores with real-time stockout alerts in under 5 minutes • GPT-Augmented Outreach: Automated scoring + messaging that closed new B2B clients in 30 days ⸻ 💬 Work With Me If… • You’re overwhelmed by repetitive ops tasks • You care about safety, oversight, and performance, not just shiny demos • You want automations that unlock 100+ hours/month in team capacity ⸻ 📅 Ready to Get Started? Book a diagnostic call. In Week 1, you’ll have something live, documented, and delivering value — so your team understands it, not just uses it.

3x Certified aws and certified databricks developer having more than 5 years in Data Analytics domain having wide variety of expertise in multi sub domain of data engineering projects including ETL/ELT data pipelines, data warehousing, delta lakes and event driven architectures. I have expertise and experience in trending technologies such as: • Python • SQL • Spark • Airflow • DBT • Snowflake • AWS s3 • AWS Lambda • AWS Athena • AWS Glue • AWS EMR • Azure Synapse Analytics • Azure Data factory • Azure Databricks • GCP Biqquery • GCP Cloud Storage • GCP Dataproc • GCP Pub/sub

I am a Professional Data person fluent in Data Analytics and Data Engineering. I turn messy data into clear insights and automate end-to-end Data-to-Decision systems. My work spans Product Analytics & Data Engineering, so I do not just analyze data; I build the pipelines, models, and dashboards that power decisions. Certifications: dbt Certified Developer TechStack Python • SQL • dbt • Shopify Analytics • Airflow • Looker Studio • Looker • n8n • PowerBI • Power Automate • Airtable •Tableau • BigQuery • GCP • LLM APIs • Excel If you need someone who understands data end-to-end and will hold themselves accountable to measurable business outcomes, let’s talk. What Else Can I Do? - Create detailed documentation for data requirements and data strategy. - Build data pipelines from scratch to meet your goals, including API-based data extraction. - Build clear visualizations that highlight the most important insights. - Automate routine workflows with Python or n8n. - Analyze Shopify data using Shopify app API (version: 2026) Feel free to reach out through Upwork messaging to get started. You’re also welcome to contact me just for ideas or a conversation, even if you’re not yet sure about the full scope of the work.

With over 8 years’ experience delivering business intelligence and analytics solutions, I help organisations turn complex, fragmented data into clear, trusted insight that drives better decisions, operational efficiency, and strategic focus. My work centres on creating a single, reliable view of performance by shaping data into consistent, analytics-ready datasets and translating them into intuitive executive dashboards. I do the T in ELT. This enables leaders to monitor outcomes, spot risks early, and take action with confidence, rather than relying on manual reports or conflicting numbers. I am recognised for bridging the gap between data and decision-making, working closely with stakeholders to ensure insights answer real business questions and support measurable outcomes. Across engagements, my work has improved data visibility and strengthened confidence in reporting. #Dimensional modelling, # Semantic Modelling,#Databricks,#Data Models,#Azure Data Studio, #SSMS Views, #Stored Procedures, #CTE's,#Views, #SSAS, #SSRS, #Power Pivot, #Power Query, #DAX, Mashup, #Azure DevOps for version control (Git)

I help businesses transform raw data into clear, actionable insights that drive smarter decisions. With 3+ years of experience, I deliver end-to-end analytics solutions — from data extraction and modeling to automated reporting and executive-ready dashboards. I work with stakeholders to define KPIs, ensure data accuracy, and build insights that create real business impact. 📊 What I Can Help You With ✔ Power BI dashboards (KPIs, trends, drill-downs, executive views) ✔ Data analysis & business intelligence ✔ Data modeling ✔ Data pipelines & automation ✔ Reporting optimization & self-service analytics 🏢 Experience Across Domains • Healthcare • E-commerce • Sales • Finance • HR • Operations 🎯 Result Reliable reporting, tailored to business needs. 📩 Let’s turn your data into insights you can trust.

I build the data infrastructure that lets businesses actually trust their data — scalable pipelines, lakehouse architectures, and real-time streaming systems that just work. In 4 years across banking, telecom, and fast-moving startups, here's what I've delivered: • Designed a Data Lakehouse using Apache Iceberg, Spark & MinIO — processing structured + unstructured data at scale • Built event-driven pipelines (Kafka → Elasticsearch) with 20% improvement in system efficiency • Created KPI dashboards used by 2,500+ employees daily, saving 20+ hours/week of manual reporting • Managed 30+ production data pipelines with high availability and scheduled reporting • Migrated large-scale Hadoop/Hive workloads to modern platforms and built production Databricks + Azure Data Factory pipelines • Automated website analytics collection using Airflow + SQL, saving cost equivalent to 3 employees per site ━━━━━━━━━━━━━━━━━━━━ WHAT I DO BEST: • Data Pipeline Development - End-to-end ETL/ELT pipelines using Python, SQL, Spark, Airflow, NiFi, and dbt - Idempotent design with retries, backfills, error handling, and data validation - Batch and near real-time (CDC) ingestion from APIs, databases, files, and streams • Data Lakehouse & Warehouse - Architecture using Databricks, Apache Iceberg, Snowflake, Synapse, Redshift, and Doris - Medallion architecture (Bronze/Silver/Gold) with schema evolution and data quality gates - Dimensional modeling, star/snowflake schemas, SCD2, and naming conventions • Microsoft / Azure Data Stack - Production pipelines with Azure Data Factory and Databricks - Synapse Analytics for warehousing and analytics workloads - Microsoft Fabric for unified data and reporting • Big Data Platforms - Hadoop, Hive, and Ambari for large-scale data processing - Hadoop-to-cloud migrations and legacy system modernization - HiveQL optimization, partitioning, and ORC/Parquet tuning • Real-Time Streaming - Kafka-based event-driven architectures feeding Elasticsearch - Stream processing with monitoring and alerting (Grafana / Loki) - Back-pressure handling and pipeline throughput tuning • Cloud Data Infrastructure - AWS (S3, Glue, Redshift, Athena, Lambda, Kinesis) setup and optimization - Cost optimization (FinOps), storage tiering, and performance tuning - Containerized workloads with Docker • BI & Dashboards - Power BI, Grafana, Kibana dashboards built for real decision-making - Data governance, security, and role-based access - KPI tracking from executive overview down to detail level • SQL & Performance Tuning - Complex queries, window functions, CTEs across PostgreSQL, MySQL, SQL Server, Oracle - Query optimization, indexing strategy, and execution-plan analysis ━━━━━━━━━━━━━━━━━━━━ MY TECH STACK: • Languages: Python (Django, Flask, FastAPI), SQL, PL/SQL, NoSQL • Data Tools: Apache Airflow, Spark/PySpark, Kafka, NiFi, dbt, Trino • Microsoft/Azure: Databricks, Azure Data Factory, Synapse Analytics, Microsoft Fabric • Big Data: Hadoop, Hive, Ambari • Cloud: AWS (S3, Lambda, Glue, Redshift, Athena, Kinesis), Docker • Warehousing & Storage: Snowflake, Apache Iceberg, MinIO, Elasticsearch, Apache Doris • Databases: PostgreSQL, MySQL, SQL Server, Oracle • BI & Monitoring: Power BI, Grafana, Kibana, Loki ━━━━━━━━━━━━━━━━━━━━ CERTIFICATIONS: • AWS Certified Solutions Architect – Associate • Astronomer Certified Apache Airflow 3 ━━━━━━━━━━━━━━━━━━━━ INDUSTRIES I'VE WORKED IN: • Banking & Fintech • Telecom • Technology Startups ━━━━━━━━━━━━━━━━━━━━ Whether you need a data pipeline built from scratch, a messy warehouse cleaned up, a Hadoop-to-cloud migration, a real-time streaming system, or a dashboard that actually gets used — message me and let's talk specifics. I respond within 2 hours.